Typically, Complex Event Processing (CEP) is an approach that aggregates information from distributed message-based systems, databases, and applications in real-time and dynamically applies rules to discern patterns and trends that may otherwise go unnoticed. This may give companies the ability to identify and even anticipate exceptions and opportunities represented by seemingly unrelated events across highly complex, distributed, and heterogeneous environments. CEP is also used to correlate, aggregate, enrich, and detect patterns in high speed streaming data in near real time. Furthermore, CEP supports streaming of unbounded data through the notion of a stream. A stream is an unbounded collection of data items and in contrast, a selection is a finite collection of data items—much like in a traditional database system. Presently, there exist various operators that convert from a stream to a relation and vice versa.
Furthermore, ISTREAM (or insert stream) is one of the operators that converts a relation to a stream. ISTREAM calculates a multiset difference of a relation as a function of time R(t) and R(t−1) taking into account all columns of a relation. As such, because all columns are taken into account, the output data may include information which is unnecessary or unwanted. Hence, these and other shortcomings in the art are remedied by the present invention.
In the appended figures, similar components and/or features may have the same numerical reference label. Further, various components of the same type may be distinguished by following the reference label by a letter that distinguishes among the similar components and/or features. If only the first numerical reference label is used in the specification, the description is applicable to any one of the similar components and/or features having the same first numerical reference label irrespective of the letter suffix.